Research Article
Multiobjective Genetic Algorithms for Reinforcing Equal Population in Congressional Districts
| Input parameters: N (archive size), T (maximum number of generations) | | Output: A (Pareto front approximation) | | (1) | | | (2) | Generate an initial population, , and external archive, | | (3) | while do | | (4) | Calculate fitness values of individuals in and | | (5) | Copy all nondominated individuals in and to | | (6) | if then | | (7) | Fill with dominated solutions in and | | (8) | end if | | (9) | if then | | (10) | Reduce by means of the truncation operator | | (11) | end if | | (12) | Create a mating pool applying binary tournament selection | | (13) | Apply crossover and mutation over the mating pool and set to the resulting population | | (14) | UpdateParetoFront(P, ) | | (15) | | | (16) | end while |
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